Code Monkey home page Code Monkey logo

fix-yahoo-finance's Introduction

Yahoo! Finance Fix for Pandas Datareader

Python version PyPi version PyPi status Travis-CI build status Star this repo Follow me on twitter

Yahoo! finance has decommissioned their historical data API, causing many programs that relied on it to stop working.

fix-yahoo-finance fixes the problem by scraping the data from Yahoo! finance and returning a Pandas DataFrame in the same format as pandas_datareader's get_data_yahoo().

By basically "hijacking" pandas_datareader.data.get_data_yahoo() method, fix-yahoo-finance's implantation is easy and only requires to import fix_yahoo_finance into your code.

Changelog »


==> Check out this Blog post for a detailed tutorial with code examples.


Quick Start

The Ticker module

The Ticker module, which allows you to access ticker data in amore Pythonic way:

import fix_yahoo_finance as yf

msft = yf.Ticker("MSFT")

# get stock info
msft.info

# get historical market data
hist = msft.history(period="max")

# show actions (dividends, splits)
msft.actions

# show dividends
msft.dividends

# show splits
msft.splits

Fetching data for multiple tickers

import fix_yahoo_finance as yf
data = yf.download("SPY AAPL", start="2017-01-01", end="2017-04-30")

I've also added some options to make life easier :)

data = yf.download(  # or pdr.get_data_yahoo(...
        # tickers list or string as well
        tickers = "SPY IWM TLT",

        # use "period" instead of start/end
        # valid periods: 1d,5d,1mo,3mo,6mo,1y,2y,5y,10y,ytd,max
        # (optional, default is '1mo')
        period = "mtd",

        # fetch data by interval (including intraday if period < 60 days)
        # valid intervals: 1m,2m,5m,15m,30m,60m,90m,1h,1d,5d,1wk,1mo,3mo
        # (optional, default is '1d')
        interval = "1m",

        # group by ticker (to access via data['SPY'])
        # (optional, default is 'column')
        group_by = 'ticker',

        # adjust all OHLC automatically
        # (optional, default is False)
        auto_adjust = True,

        # download pre/post regular market hours data
        # (optional, default is False)
        prepost = True
    )

pandas_datareader override

from pandas_datareader import data as pdr

import fix_yahoo_finance as yf
yf.pdr_override() # <== that's all it takes :-)

# download dataframe
data = pdr.get_data_yahoo("SPY", start="2017-01-01", end="2017-04-30")

Installation

Install fix_yahoo_finance using pip:

$ pip install fix_yahoo_finance --upgrade --no-cache-dir

Requirements

Optional (if you want to use pandas_datareader)

Legal Stuff

fix-yahoo-finance is distributed under the Apache Software License. See the LICENSE.txt file in the release for details.

P.S.

Please drop me an note with any feedback you have.

Ran Aroussi

fix-yahoo-finance's People

Contributors

ranaroussi avatar jonathanng avatar manan904 avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.